Exploration of Ticket/Label Based Representation by Social Re-Grading

Social media sharing websites like flickr shares images using their respective tags. According to this tag, images can be retrieved and this process is known as tag-based image retrieval. However, making the tagged images as top ranked result relevant is challenging. In this paper, we propose a social re-grading system for tag-based image search with the consideration of image retrieval and diversity. Images are re-graded according to their visual information, semantic information, and social clues. The initial results include images contributed by different social users. Usually each user contributes multiple images by their views. First, we sort these images by inter- user re-grading and intra-user re-grading. Each userís contributed image come higher position and thus images are stored in social image dataset in the database to sort images and it is also re-graded by tag-based image search. Experimental results on a flickr dataset show that our social re-grading method is effective and efficient.